Development of VISNIR predictive regression models for ultimate pH, meat tenderness (shear force) and intramuscular fat content of Australian lamb

Matthew I Knight; Nick Linden; Eric N Ponnampalam; Matthew G Kerr; Wayne G Brown; David L Hopkins; Stuart Baud; Alex J Ball; Claus Borggaard; Ian Wesley

doi:10.1016/j.meatsci.2019.05.009

Development of VISNIR predictive regression models for ultimate pH, meat tenderness (shear force) and intramuscular fat content of Australian lamb

Meat Sci. 2019 Sep:155:102-108. doi: 10.1016/j.meatsci.2019.05.009. Epub 2019 May 11.

Authors

Affiliations

¹ Agriculture Victoria Research, Department of Economic Development, Jobs, Transport and Resources, 915 Mount Napier Road, Hamilton, VIC 3300, Australia. Electronic address: matthew.knight@ecodev.vic.gov.au.
² Agriculture Victoria Research, Department of Economic Development, Jobs, Transport and Resources, 124 Chiltern Valley Road, Rutherglen, VIC 3685, Australia.
³ Agriculture Victoria Research, Department of Economic Development, Jobs, Transport and Resources, 5 Ring Road, Bundoora, VIC 3083, Australia.
⁴ Centre for Red Meat and Sheep Development, NSW Department of Primary Industries, PO Box 129, Cowra, NSW 2794, Australia.
⁵ Baud and Associates Pty. Ltd., Bairnsdale, VIC 3875, Australia.
⁶ Rural Analytics, 19 Eleanor Close, Armidale, NSW 2350, Australia.
⁷ Danish Meat Research Institute, Gregersensvej 9, 2630 Taastrup, Denmark.
⁸ Australian Export Grains Innovation Centre, PO Box 711, North Ryde BC, NSW 1670, Australia.

PMID: 31102991
DOI: 10.1016/j.meatsci.2019.05.009

Abstract

This study investigated the effectiveness of visible-near-infrared (VISNIR) spectroscopy at classifying Australian lamb for: a) ultimate pH (pH 24), b) meat tenderness (i.e. shear force at day 5 of ageing, SF5) and c) intramuscular fat (IMF) content at 24 h post-slaughter using a custom-made handheld probe coupled with the ASD Labspec Pro instrument. VISNIR predictive regression models were developed. In the loin muscle (M. longissimus thoracis et lumborum), the models classified the predicted pH 24, SF5 and IMF content at above or below a threshold value with 94%, 98% and 88% accuracy, respectively. The observed difference between the actual and predicted value (i.e. the standard error of cross validation, SECV) for ultimate pH and IMF content are approaching accuracies required to attain highly reliable Meat Standards Australia grading standards. However, further development is required to improve the SECV for SF5.

Keywords: Lamb grading; MSA sheep meat; Meat quality; Objective measurement.

MeSH terms

Adipose Tissue
Animals
Australia
Female
Food Quality
Hydrogen-Ion Concentration
Male
Models, Statistical
Red Meat / analysis*
Shear Strength
Sheep, Domestic
Spectroscopy, Near-Infrared / instrumentation
Spectroscopy, Near-Infrared / methods*